</default>
  </defaults>

  <classes>
    <class rootElement="true" xml.tagName="extensions" xsd.compositor="sequence">
      <name>CoreExtensions</name>
      <description>Extensions to load.</description>
      <version>1.0.0+</version>
      <fields>
        <field>
          <name>extensions</name>
          <description>A set of build extensions to use from this project.</description>

   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

            try {
                mavenWrapperPropertyFileInputStream = new FileInputStream(mavenWrapperPropertyFile);
                Properties mavenWrapperProperties = new Properties();
                mavenWrapperProperties.load(mavenWrapperPropertyFileInputStream);
                url = mavenWrapperProperties.getProperty(PROPERTY_NAME_WRAPPER_URL, url);
            } catch (IOException e) {

        Thread.currentThread().interrupt() // Retain interrupted status.
      }
    }

    if (!::bytes.isInitialized) {
      // May have failed with an IOException
      throw IllegalStateException("Unable to load $path resource.").apply {
        initCause(readFailure)
      }
    }
  }

  abstract val path: Any

  /**
   * Reads the public suffix list treating the operation as uninterruptible. We always want to read

		tx.Statement.DB = tx
	}

	if config.Context != nil {
		tx.Statement.Context = config.Context
	}

	if config.PrepareStmt {
		var preparedStmt *PreparedStmtDB

		if v, ok := db.cacheStore.Load(preparedStmtDBKey); ok {
			preparedStmt = v.(*PreparedStmtDB)
		} else {
			preparedStmt = NewPreparedStmtDB(db.ConnPool, db.PrepareStmtMaxSize, db.PrepareStmtTTL)
			db.cacheStore.Store(preparedStmtDBKey, preparedStmt)

     * dependency injection is complete.
     */
    @PostConstruct
    public void register() {
        if (logger.isInfoEnabled()) {
            logger.info("Load {}", this.getClass().getSimpleName());
        }
        dictionaryManager.addCreator(this);
    }

    /**
     * Creates a new {@link SynonymFile} instance.
     *

        File pom0 = new File(localRepo, "p0/pom.xml");

        File pom0Basedir = pom0.getParentFile();

        File pom1 = new File(pom0Basedir, "p1/pom.xml");

        // load everything...
        MavenProject project0 = getProject(pom0);
        MavenProject project1 = getProject(pom1);

        assertEquals(pom0Basedir, project1.getParent().getBasedir());
    }

    MINIO_CI_CD: 1
  healthcheck:
    test: ["CMD", "mc", "ready", "local"]
    interval: 5s
    timeout: 5s
    retries: 5

# starts 4 docker containers running minio server instances.
# using nginx reverse proxy, load balancing, you can access
# it through port 9000.
services:
  minio1:
    <<: *minio-common
    hostname: minio1
    volumes:
      - data1-1:/data1
      - data1-2:/data2
      - data1-3:/data3

//
// floating point conditional branch
//
//	LBRA rel
label4:
	BFPT	1(PC)	// BFPT 1(PC)			// 4501000100000000
	BFPT	label4	// BFPT 24			// 4501fffd00000000

//inst:
//
// load ints and bytes
//
//	LMOVV rreg ',' rreg
//	{
//		outcode(int($1), &$2, 0, &$4);
//	}
	MOVV	R25, R17	// 00198825
	MOVV	R1, R2		// 00011025
	MOVV	LO, R1		// 00000812
	MOVV	HI, R1		// 00000810

marked `PENDING` or `FAILED` are re-queued for replication.

Replication speed depends on the cluster load, number of objects in the object store as well as storage speed. In addition, any bandwidth limits set via `mc admin bucket remote add` could also contribute to replication speed. The number of workers used for replication defaults to 100. Based on network bandwidth and system load, the number of workers used in replication can be configured using `mc admin config set alias api` to set the...